zsxkib/instant-id:6af8583c – Run with an API on Replicate

Version

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zsxkib /instant-id:6af8583c

Playground API

Input

image

*file

Preview

Input face image

pose_image

file

(Optional) reference pose image

prompt

string

Shift + Return to add a new line

masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polishedmasterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished

Input prompt

Default: "a person"

negative_prompt

string

Shift + Return to add a new line

(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green

Input Negative Prompt

Default: ""

sdxl_weights

string

Pick which base weights you want to use

Default: "stable-diffusion-xl-base-1.0"

width

integer

(minimum: 512, maximum: 4096)

Width of output image

Default: 640

height

integer

(minimum: 512, maximum: 4096)

Height of output image

Default: 640

scheduler

string

Scheduler

Default: "EulerDiscreteScheduler"

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 30

guidance_scale

number

(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 7.5

ip_adapter_scale

number

(minimum: 0, maximum: 1.5)

Scale for image adapter strength (for detail)

Default: 0.8

controlnet_conditioning_scale

number

(minimum: 0, maximum: 1.5)

Scale for IdentityNet strength (for fidelity)

Default: 0.8

enable_pose_controlnet

boolean

Enable Openpose ControlNet, overrides strength if set to false

Default: true

pose_strength

number

(minimum: 0, maximum: 1)

Openpose ControlNet strength, effective only if `enable_pose_controlnet` is true

Default: 0.4

enable_canny_controlnet

boolean

Enable Canny ControlNet, overrides strength if set to false

Default: false

canny_strength

number

(minimum: 0, maximum: 1)

Canny ControlNet strength, effective only if `enable_canny_controlnet` is true

Default: 0.3

enable_depth_controlnet

boolean

Enable Depth ControlNet, overrides strength if set to false

Default: false

depth_strength

number

(minimum: 0, maximum: 1)

Depth ControlNet strength, effective only if `enable_depth_controlnet` is true

Default: 0.5

enable_lcm

boolean

Enable Fast Inference with LCM (Latent Consistency Models) - speeds up inference steps, trade-off is the quality of the generated image. Performs better with close-up portrait face images

Default: false

lcm_num_inference_steps

integer

(minimum: 1, maximum: 10)

Only used when `enable_lcm` is set to True, Number of denoising steps when using LCM

Default: 5

lcm_guidance_scale

number

(minimum: 1, maximum: 20)

Only used when `enable_lcm` is set to True, Scale for classifier-free guidance when using LCM

Default: 1.5

enhance_nonface_region

boolean

Enhance non-face region

Default: true

seed

integer

Random seed. Leave blank to randomize the seed

disable_safety_checker

boolean

Disable safety checker for generated images

Default: false

Run this model in Node.js with one line of code:

npx create-replicate --model=zsxkib/instant-id

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "zsxkib/instant-id:6af8583c541261472e92155d87bba80d5ad98461665802f2ba196ac099aaedc9",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KMB8vhqlXLdAcElPz8lcQhtJrzzOzJEsdwWfkXAyuhotbKwq/meisje_met_de_parel.webp",
      width: 640,
      height: 640,
      prompt: "masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished",
      scheduler: "EulerDiscreteScheduler",
      enable_lcm: false,
      sdxl_weights: "nightvision-xl-0791",
      pose_strength: 0.4,
      canny_strength: 0.3,
      depth_strength: 0.5,
      guidance_scale: 5,
      negative_prompt: "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
      ip_adapter_scale: 0.8,
      lcm_guidance_scale: 1.5,
      num_inference_steps: 30,
      enable_pose_controlnet: true,
      enhance_nonface_region: true,
      enable_canny_controlnet: true,
      enable_depth_controlnet: false,
      lcm_num_inference_steps: 5,
      controlnet_conditioning_scale: 0.8
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "zsxkib/instant-id:6af8583c541261472e92155d87bba80d5ad98461665802f2ba196ac099aaedc9",
    input={
        "image": "https://replicate.delivery/pbxt/KMB8vhqlXLdAcElPz8lcQhtJrzzOzJEsdwWfkXAyuhotbKwq/meisje_met_de_parel.webp",
        "width": 640,
        "height": 640,
        "prompt": "masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished",
        "scheduler": "EulerDiscreteScheduler",
        "enable_lcm": False,
        "sdxl_weights": "nightvision-xl-0791",
        "pose_strength": 0.4,
        "canny_strength": 0.3,
        "depth_strength": 0.5,
        "guidance_scale": 5,
        "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
        "ip_adapter_scale": 0.8,
        "lcm_guidance_scale": 1.5,
        "num_inference_steps": 30,
        "enable_pose_controlnet": True,
        "enhance_nonface_region": True,
        "enable_canny_controlnet": True,
        "enable_depth_controlnet": False,
        "lcm_num_inference_steps": 5,
        "controlnet_conditioning_scale": 0.8
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "6af8583c541261472e92155d87bba80d5ad98461665802f2ba196ac099aaedc9",
    "input": {
      "image": "https://replicate.delivery/pbxt/KMB8vhqlXLdAcElPz8lcQhtJrzzOzJEsdwWfkXAyuhotbKwq/meisje_met_de_parel.webp",
      "width": 640,
      "height": 640,
      "prompt": "masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished",
      "scheduler": "EulerDiscreteScheduler",
      "enable_lcm": false,
      "sdxl_weights": "nightvision-xl-0791",
      "pose_strength": 0.4,
      "canny_strength": 0.3,
      "depth_strength": 0.5,
      "guidance_scale": 5,
      "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
      "ip_adapter_scale": 0.8,
      "lcm_guidance_scale": 1.5,
      "num_inference_steps": 30,
      "enable_pose_controlnet": true,
      "enhance_nonface_region": true,
      "enable_canny_controlnet": true,
      "enable_depth_controlnet": false,
      "lcm_num_inference_steps": 5,
      "controlnet_conditioning_scale": 0.8
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/zsxkib/instant-id@sha256:6af8583c541261472e92155d87bba80d5ad98461665802f2ba196ac099aaedc9 \
  -i 'image="https://replicate.delivery/pbxt/KMB8vhqlXLdAcElPz8lcQhtJrzzOzJEsdwWfkXAyuhotbKwq/meisje_met_de_parel.webp"' \
  -i 'width=640' \
  -i 'height=640' \
  -i 'prompt="masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished"' \
  -i 'scheduler="EulerDiscreteScheduler"' \
  -i 'enable_lcm=false' \
  -i 'sdxl_weights="nightvision-xl-0791"' \
  -i 'pose_strength=0.4' \
  -i 'canny_strength=0.3' \
  -i 'depth_strength=0.5' \
  -i 'guidance_scale=5' \
  -i 'negative_prompt="(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green"' \
  -i 'ip_adapter_scale=0.8' \
  -i 'lcm_guidance_scale=1.5' \
  -i 'num_inference_steps=30' \
  -i 'enable_pose_controlnet=true' \
  -i 'enhance_nonface_region=true' \
  -i 'enable_canny_controlnet=true' \
  -i 'enable_depth_controlnet=false' \
  -i 'lcm_num_inference_steps=5' \
  -i 'controlnet_conditioning_scale=0.8'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/zsxkib/instant-id@sha256:6af8583c541261472e92155d87bba80d5ad98461665802f2ba196ac099aaedc9
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "image": "https://replicate.delivery/pbxt/KMB8vhqlXLdAcElPz8lcQhtJrzzOzJEsdwWfkXAyuhotbKwq/meisje_met_de_parel.webp",
      "width": 640,
      "height": 640,
      "prompt": "masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished",
      "scheduler": "EulerDiscreteScheduler",
      "enable_lcm": false,
      "sdxl_weights": "nightvision-xl-0791",
      "pose_strength": 0.4,
      "canny_strength": 0.3,
      "depth_strength": 0.5,
      "guidance_scale": 5,
      "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
      "ip_adapter_scale": 0.8,
      "lcm_guidance_scale": 1.5,
      "num_inference_steps": 30,
      "enable_pose_controlnet": true,
      "enhance_nonface_region": true,
      "enable_canny_controlnet": true,
      "enable_depth_controlnet": false,
      "lcm_num_inference_steps": 5,
      "controlnet_conditioning_scale": 0.8
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-02-06T14:05:12.172734Z",
  "created_at": "2024-02-06T14:04:25.076266Z",
  "data_removed": false,
  "error": null,
  "id": "r766fk3ban74fwagxopi7mqsxe",
  "input": {
    "image": "https://replicate.delivery/pbxt/KMB8vhqlXLdAcElPz8lcQhtJrzzOzJEsdwWfkXAyuhotbKwq/meisje_met_de_parel.webp",
    "width": 640,
    "height": 640,
    "prompt": "masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished",
    "scheduler": "EulerDiscreteScheduler",
    "enable_lcm": false,
    "sdxl_weights": "nightvision-xl-0791",
    "pose_strength": 0.4,
    "canny_strength": 0.3,
    "depth_strength": 0.5,
    "guidance_scale": 5,
    "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
    "ip_adapter_scale": 0.8,
    "lcm_guidance_scale": 1.5,
    "num_inference_steps": 30,
    "enable_pose_controlnet": true,
    "enhance_nonface_region": true,
    "enable_canny_controlnet": true,
    "enable_depth_controlnet": false,
    "lcm_num_inference_steps": 5,
    "controlnet_conditioning_scale": 0.8
  },
  "logs": "Using seed: 31094\ndownloading url:  https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar\ndownloading to:  checkpoints/models--stablediffusionapi--nightvision-xl-0791\n2024-02-06T14:04:25Z | INFO  | [ Initiating ] dest=checkpoints/models--stablediffusionapi--nightvision-xl-0791 minimum_chunk_size=150M url=https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar\n2024-02-06T14:04:33Z | INFO  | [ Complete ] dest=checkpoints/models--stablediffusionapi--nightvision-xl-0791 size=\"6.9 GB\" total_elapsed=8.690s url=https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar\ndownloading took:  9.307956218719482\n[~] Loading new SDXL weights: checkpoints/models--stablediffusionapi--nightvision-xl-0791/\nKeyword arguments {'safety_checker': None} are not expected by StableDiffusionXLInstantIDPipeline and will be ignored.\nLoading pipeline components...:   0%|          | 0/7 [00:00<?, ?it/s]\nLoading pipeline components...:  14%|█▍        | 1/7 [00:00<00:02,  2.25it/s]\nLoading pipeline components...:  43%|████▎     | 3/7 [00:00<00:00,  5.65it/s]\nLoading pipeline components...:  57%|█████▋    | 4/7 [00:00<00:00,  4.84it/s]\nLoading pipeline components...:  86%|████████▌ | 6/7 [00:02<00:00,  1.65it/s]\nLoading pipeline components...: 100%|██████████| 7/7 [00:02<00:00,  2.42it/s]\n[~] Seting up LCM (just in case)\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/insightface/utils/transform.py:68: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.\nTo use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.\nP = np.linalg.lstsq(X_homo, Y)[0].T # Affine matrix. 3 x 4\nStart inference...\n[Debug] Prompt: masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished,\n[Debug] Neg Prompt: (lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green\n  0%|          | 0/30 [00:00<?, ?it/s]\n  3%|▎         | 1/30 [00:00<00:16,  1.79it/s]\n  7%|▋         | 2/30 [00:01<00:15,  1.79it/s]\n 10%|█         | 3/30 [00:01<00:15,  1.79it/s]\n 13%|█▎        | 4/30 [00:02<00:14,  1.78it/s]\n 17%|█▋        | 5/30 [00:02<00:14,  1.78it/s]\n 20%|██        | 6/30 [00:03<00:13,  1.78it/s]\n 23%|██▎       | 7/30 [00:03<00:12,  1.78it/s]\n 27%|██▋       | 8/30 [00:04<00:12,  1.78it/s]\n 30%|███       | 9/30 [00:05<00:11,  1.78it/s]\n 33%|███▎      | 10/30 [00:05<00:11,  1.77it/s]\n 37%|███▋      | 11/30 [00:06<00:10,  1.77it/s]\n 40%|████      | 12/30 [00:06<00:10,  1.77it/s]\n 43%|████▎     | 13/30 [00:07<00:09,  1.77it/s]\n 47%|████▋     | 14/30 [00:07<00:09,  1.77it/s]\n 50%|█████     | 15/30 [00:08<00:08,  1.77it/s]\n 53%|█████▎    | 16/30 [00:09<00:07,  1.77it/s]\n 57%|█████▋    | 17/30 [00:09<00:07,  1.77it/s]\n 60%|██████    | 18/30 [00:10<00:06,  1.77it/s]\n 63%|██████▎   | 19/30 [00:10<00:06,  1.77it/s]\n 67%|██████▋   | 20/30 [00:11<00:05,  1.77it/s]\n 70%|███████   | 21/30 [00:11<00:05,  1.77it/s]\n 73%|███████▎  | 22/30 [00:12<00:04,  1.77it/s]\n 77%|███████▋  | 23/30 [00:12<00:03,  1.77it/s]\n 80%|████████  | 24/30 [00:13<00:03,  1.77it/s]\n 83%|████████▎ | 25/30 [00:14<00:02,  1.77it/s]\n 87%|████████▋ | 26/30 [00:14<00:02,  1.77it/s]\n 90%|█████████ | 27/30 [00:15<00:01,  1.77it/s]\n 93%|█████████▎| 28/30 [00:15<00:01,  1.77it/s]\n 97%|█████████▋| 29/30 [00:16<00:00,  1.77it/s]\n100%|██████████| 30/30 [00:16<00:00,  1.77it/s]\n100%|██████████| 30/30 [00:16<00:00,  1.77it/s]\nNSFW content detected: False",
  "metrics": {
    "predict_time": 47.065249,
    "total_time": 47.096468
  },
  "output": [
    "https://replicate.delivery/pbxt/AhtyoJfezztMUEvhkEXKKdeefqHLLqGF3emHkL7fQdIXLdfTSA/out_0.png"
  ],
  "started_at": "2024-02-06T14:04:25.107485Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/r766fk3ban74fwagxopi7mqsxe",
    "cancel": "https://api.replicate.com/v1/predictions/r766fk3ban74fwagxopi7mqsxe/cancel"
  },
  "version": "6af8583c541261472e92155d87bba80d5ad98461665802f2ba196ac099aaedc9"
}

Generated in

47.1 seconds

Tweak itReport

Using seed: 31094
downloading url:  https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar
downloading to:  checkpoints/models--stablediffusionapi--nightvision-xl-0791
2024-02-06T14:04:25Z | INFO  | [ Initiating ] dest=checkpoints/models--stablediffusionapi--nightvision-xl-0791 minimum_chunk_size=150M url=https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar
2024-02-06T14:04:33Z | INFO  | [ Complete ] dest=checkpoints/models--stablediffusionapi--nightvision-xl-0791 size="6.9 GB" total_elapsed=8.690s url=https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar
downloading took:  9.307956218719482
[~] Loading new SDXL weights: checkpoints/models--stablediffusionapi--nightvision-xl-0791/
Keyword arguments {'safety_checker': None} are not expected by StableDiffusionXLInstantIDPipeline and will be ignored.
Loading pipeline components...:   0%|          | 0/7 [00:00<?, ?it/s]
Loading pipeline components...:  14%|█▍        | 1/7 [00:00<00:02,  2.25it/s]
Loading pipeline components...:  43%|████▎     | 3/7 [00:00<00:00,  5.65it/s]
Loading pipeline components...:  57%|█████▋    | 4/7 [00:00<00:00,  4.84it/s]
Loading pipeline components...:  86%|████████▌ | 6/7 [00:02<00:00,  1.65it/s]
Loading pipeline components...: 100%|██████████| 7/7 [00:02<00:00,  2.42it/s]
[~] Seting up LCM (just in case)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/insightface/utils/transform.py:68: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
P = np.linalg.lstsq(X_homo, Y)[0].T # Affine matrix. 3 x 4
Start inference...
[Debug] Prompt: masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished,
[Debug] Neg Prompt: (lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green
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NSFW content detected: False